Articles | Volume 17, issue 10
https://doi.org/10.5194/essd-17-5377-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-5377-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data review article
| 
16 Oct 2025
Data review article |
| 16 Oct 2025
| 16 Oct 2025
State of Wildfires 2024–2025
Water and Climate Science, UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Chantelle Burton
CORRESPONDING AUTHOR
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Francesca Di Giuseppe
CORRESPONDING AUTHOR
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
Matthew W. Jones
CORRESPONDING AUTHOR
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
Maria L. F. Barbosa
Water and Climate Science, UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Esther Brambleby
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
Joe R. McNorton
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
Zhongwei Liu
National Centre for Earth Observation, University of Leicester, Space Park Leicester, 92 Corporation Road, Space City, Leicester, LE4 5SP, UK
Anna S. I. Bradley
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Katie Blackford
Water and Climate Science, UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Department of Life Sciences, Imperial College London, Chemistry Building CHEM062, South Kensington, London, SW7 2AZ, UK
Eleanor Burke
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Andrew Ciavarella
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Enza Di Tomaso
European Centre for Medium-Range Weather Forecasts, Robert-Schuman-Platz 3, 53175 Bonn, Germany
Jonathan Eden
Centre for Agroecology, Water and Resilience, Coventry University, Wolston Ln, Ryton-on-Dunsmore, Coventry, CV8 3LG, UK
Igor José M. Ferreira
Earth Observation and Geoinformatics, National Institute for Space Research (INPE), Astronautas Avenue 1758, São José dos Campos, 12227-010, Brazil
Lukas Fiedler
Institute of Oceanography, Center for Earth System Research and Sustainability, University of Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Andrew J. Hartley
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Theodore R. Keeping
Centre for Environmental Policy, Imperial College London, Weeks Building, 16–18 Prince's Gardens, London, SW7 1NE, UK
Leverhulme Centre for Wildfires, Environment and Society, Imperial College London, South Kensington, London, SW7 2BW, UK
Seppe Lampe
Water and Climate, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Anna Lombardi
European Centre for Medium-Range Weather Forecasts, Robert-Schuman-Platz 3, 53175 Bonn, Germany
Guilherme Mataveli
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
Earth Observation and Geoinformatics, National Institute for Space Research (INPE), Astronautas Avenue 1758, São José dos Campos, 12227-010, Brazil
Yuquan Qu
Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1100, Amsterdam, 1081 HV, the Netherlands
Patrícia S. Silva
School of the Environment, Yale University, 195 Prospect St, New Haven, CT 06511, USA
Fiona R. Spuler
Department of Meteorology, University of Reading, Brian Hoskins Building, Whiteknights Road, Earley Gate, Reading, RG6 6ET, UK
The Alan Turing Institute, British Library, 96 Euston Rd., London, NW1 2DB, UK
Carmen B. Steinmann
Institute for Environmental Decisions, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss, Operation Center 1, P.O. Box 257, 8058 Zurich Airport, Switzerland
Miguel Ángel Torres-Vázquez
Environmental Remote Sensing Research Group, Department of Geology, Geography and Environment, Universidad de Alcalá, Calle Colegios 2, Alcalá de Henares 28801, Spain
Renata Veiga
Laboratory for Environmental Satellite Applications (LASA), Department of Meteorology, Federal University of Rio de Janeiro, 21941-916, Rio de Janeiro, RJ, Brazil
Dave van Wees
BeZero Carbon Ltd, 25 Christopher Street, London, EC2A 2BS, UK
Jakob B. Wessel
Department of Mathematics and Statistics, University of Exeter, Harrison Building, University of Exeter, North Park Road, EX4 4QF, Exeter, UK
Emily Wright
Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Bibiana Bilbao
Biology, Departamento de Estudios Ambientales, Universidad Simón Bolívar, Valle de Sartenejas, Aartado 89000, Caracas, Venezuela
UMR Art-Dev 5281, Université Paul Valéry Montpellier, Site Saint-Charles, France, UMR 5281, Site Saint-Charles 1, Rue du Professeur Henri Serre, 34090 Montpellier, France
Mathieu Bourbonnais
Earth, Environmental and Geographic Sciences, University of British Columbia – Okanagan, 1177 University Way, Kelowna, BC, V1V 1V7, Canada
Department of Geography, University of Hong Kong, 10F, The Jockey Club Tower, Centennial Campus, Pokfulam Road, Hong Kong SAR, China
Carlos M. Di Bella
Departamento de Métodos Cuantitativos y Sistemas de Información, University of Buenos Aires, Av. San Martin 4453 (1417), CABA, Argentina
IFEVA (Agricultural Physiology and Ecology Research Institute), Av. San Martin 4453 (1417), CABA, Argentina
Kebonye Dintwe
Department of Environmental Science, University of Botswana, Plot 4775 Notwane Rd, Gaborone, Botswana
Victoria M. Donovan
West Florida Research and Education Center, School of Forest, Fisheries, and Geomatics Sciences, University of Florida, 5988 Highway 90, Milton, FL 32583, USA
Sarah Harris
Fire Risk, Research and Community Preparedness, Country Fire Authority, Burwood East, Victoria, Australia
Elena A. Kukavskaya
Laboratory of Experimental and Applied Ecology, V.N. Sukachev Institute of Forest Siberian Branch of the Russian Academy of Sciences – separate subdivision of the FRC KSC SB RAS, 50/28 Akademgorodok, Krasnoyarsk, 660036, Russian Federation
Aya Brigitte N'Dri
Department of Natural Sciences, Nangui Abrogoua University, 02 BP 801 Abidjan 02, Côte d'Ivoire
Cristina Santín
Research Institute of Biodiversity (IMIB), CSIC-University of Oviedo-Principality of Asturias, IMIB, Research Building, Mieres Campus, Mieres, 33600 Spain
Biosciences, Swansea University, Wallace Building, Singleton Campus, Swansea, SA2 8PP, UK
Galia Selaya
Research and action, ECOSCONSULT, Calle Tte. H. Balcazar No. 24, Santa Cruz de la Sierra, Bolivia
Research, Fundacion Innova, Calle Tte. H. Balcazar No. 24, Santa Cruz de la Sierra, Bolivia
Johan Sjöström
Fire and Safety, RISE Research institutes of Sweden, Box 857, 51515 Borås, Sweden
John T. Abatzoglou
School of Engineering, University of California, Merced, 5200 N Lake Rd, Merced, CA 95343, USA
Niels Andela
BeZero Carbon Ltd, 25 Christopher Street, London, EC2A 2BS, UK
Rachel Carmenta
Tyndall Centre for Climate Change Research, School of Global Development, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
Emilio Chuvieco
Environmental Remote Sensing Research Group, Department of Geology, Geography and Environment, Universidad de Alcalá, Calle Colegios 2, Alcalá de Henares 28801, Spain
Louis Giglio
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Douglas S. Hamilton
Marine, Earth, and Atmospheric Science, North Carolina State University, 2800 Faucette Drive, Raleigh, NC 27603, USA
Stijn Hantson
Program in Earth System Sciences, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
Sarah Meier
Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter, Rennes Drive, Exeter, EX4 4ST, UK
Mark Parrington
European Centre for Medium-Range Weather Forecasts, Robert-Schuman-Platz 3, 53175 Bonn, Germany
Mojtaba Sadegh
Department of Civil Engineering, Boise State University, Boise, ID, USA
Jesus San-Miguel-Ayanz
Disaster Risk Management Unit (E.1), Directorate E (Space, Security, and Migration), European Commission Joint Research Centre, European Commission, Rue du Champ de Mars 21, 1050 Brussels, Belgium
Fernando Sedano
Disaster Risk Management Unit (E.1), Directorate E (Space, Security, and Migration), European Commission Joint Research Centre, European Commission, Rue du Champ de Mars 21, 1050 Brussels, Belgium
Marco Turco
Regional Atmospheric Modelling (MAR) Group, Regional Campus of International Excellence Campus Mare Nostrum (CEIR), Department of Geography, University of Hong Kong, Hong Kong SAR, China
Guido R. van der Werf
Meteorology and Air Quality, Wageningen University and Research, Droevendaalsesteeg 3-3 A, 6708 PB, Wageningen, the Netherlands
Sander Veraverbeke
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1100, Amsterdam, 1081 HV, the Netherlands
Liana O. Anderson
Cemaden/MCTI, 500 – Distrito de Eugênio de Melo, São José dos Campos – São Paulo, Brazil
Hamish Clarke
FLARE Wildfire Research, School of Agriculture, Food and Ecosystem Sciences, University of Melbourne, Grattan St, Parkville, 3010, Australia
Paulo M. Fernandes
ForestWISE – Collaborative Laboratory for Integrated Forest and Fire Management, Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, Vila Real, 5000-801, Portugal
Crystal A. Kolden
Wildfire Resilience Center, School of Engineering, University of California, 5200 N Lake Rd, Merced, CA 95343, USA
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Anne-Wil van den Berg, Joram J. D. Hooghiem, Auke M. van der Woude, Pieter Rijsdijk, Roland Vernooij, Santiago Botía, Guido R. van der Werf, John B. Miller, Ingrid T. Luijkx, Maarten C. Krol, and Wouter Peters
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Shrutika Wagh, Luana S. Basso, Ayan F. Fleischmann, João Henrique Fernandes Amaral, John Melack, Jost Larvic, David Walter, Stijn Hantson, Julia Marshall, Chris Wilson, Youmi Oh, Lori Bruhwiler, John B. Miller, Corinne Vigouroux, Christian Rödenbeck, and Santiago Botía
EGUsphere, https://doi.org/10.5194/egusphere-2026-5245, https://doi.org/10.5194/egusphere-2026-5245, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We estimated methane emissions from the Amazon, Orinoco, and Paraná river basins using the Jena CarboScope global inversion system. We included Amazon measurements to evaluate their effect on the results. Adding them led to a large adjustment in estimated wetland emissions and strongly influenced the Amazon estimate. Without these measurements, the Amazon estimate increased by about 75 %. Our findings highlight the need to maintain and expand measurements across tropical South America.
Joe McNorton, Edward Comyn-Platt, Francesca Di Giuseppe, Chiara Cagnazzo, and Chris Barnard
EGUsphere, https://doi.org/10.5194/egusphere-2026-5374, https://doi.org/10.5194/egusphere-2026-5374, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Sparky-Climate reconstructs and projects global burned area and vegetation fuel conditions from 1950 to 2100. Although global burned area declines in all scenarios, this masks contrasting regional changes. Savanna burning declines while temperate and boreal forests show increasing burned area and more frequent extreme wildfire behaviour, especially under higher emissions. The dataset supports assessment of future carbon stocks, wildfire exposure risk and wildfire emissions.
Li Xu, Qi Tang, Qing Zhu, William J. Riley, Guido R. van der Werf, Yang Chen, Michael J. Prather, and James T. Randerson
EGUsphere, https://doi.org/10.5194/egusphere-2026-4288, https://doi.org/10.5194/egusphere-2026-4288, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Using the E3SM version 3 model with interactive chemistry, this study shows that wildfires substantially perturb global and regional tropospheric chemistry and modify radiative effects through aerosol and ozone interactions, with particularly strong impacts in tropical fire regions. By connecting wildfire emissions with changes in atmospheric composition, radiation, and climate, this study provides important insights on how the atmosphere responds to changing fire activities.
Cinzia Mazzetti, Hannah Cloke, Dai Yamazaki, Gianpaolo Balsamo, Souhail Boussetta, Jasper Denissen, Michel Wortmann, Gabriele Arduini, Gurpreet Dass, Joe McNorton, Anna Agusti-Panareda, Maliko Tanguy, Ervin Zsoter, Margarita Choulga, Emanuel Dutra, Florian Pappenberger, Christoph Rüdiger, and Christel Prudhomme
EGUsphere, https://doi.org/10.5194/egusphere-2026-4305, https://doi.org/10.5194/egusphere-2026-4305, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Rivers are an essential component of the water cycle, yet many Earth system and weather prediction models do not explicitly represent river flow. We integrated a global river model into ECMWF's forecasting system, enabling the simulation of river discharge, water levels, and flooding within a single operational framework. This development lays the foundation for future land–river–atmosphere interactions, paving the way for more complete Earth system models and improved predictions.
Inika Taylor, Douglas I. Kelley, Camilla Mathison, Karina E. Bett-Williams, Andrew J. Hartley, Richard A. Betts, Chantelle Burton, and Maria L. F. Barbosa
Nat. Hazards Earth Syst. Sci., 26, 4257–4289, https://doi.org/10.5194/nhess-26-4257-2026, https://doi.org/10.5194/nhess-26-4257-2026, 2026
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We present future climate change projections that show increasing fire danger worldwide. Focusing on Australia, Brazil, and the USA, we show that limiting warming to 2 °C reduces the increase in fire danger. However, fire seasons still lengthen and intensify even at 1.5 °C, demonstrating the need for mitigation to limit impacts and adaptation to manage residual risk. Low-fire danger periods persist, but we show their timing and duration will shift and must be considered in fire management.
Xiaoying Shi, Daniel M. Ricciuto, Yaoping Wang, Joe R. Melton, Fortunat Joos, Yiqi Luo, Xiaofeng Xu, Dafeng Hui, Qianlai Zhuang, Chunjing Qiu, Hongxing He, Siya Shao, Xingjie Lu, Yongjiu Dai, Akihiko Ito, Qing Sun, Nitin Chaudhary, Ayesha Hussain, Mousong Wu, Jian Zhou, Jingwei Zhang, Ye Yuan, Rachael H. Turton, Eleanor J. Burke, Jiafu Mao, Yuefeng Hao, Natalie A. Griffiths, Verity Salmon, Paul J. Hanson, Melanie A. Mayes, and Peter E. Thornton
EGUsphere, https://doi.org/10.5194/egusphere-2026-5193, https://doi.org/10.5194/egusphere-2026-5193, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Northern peatlands store vast amounts of carbon, but their response to climate change remains uncertain. We compared 15 ecosystem models with observations from a long-term warming and elevated carbon dioxide experiment in Minnesota. Models differed widely in their carbon responses, reflecting differences in ecosystem processes and model parameters. The results identify priorities for improving peatland models and projections of future carbon–climate feedbacks.
Natalie Mahowald, Hannah Liddy, Jennifer Marlon, Kostas Tsigaridis, Gisela Winckler, Douglas Hamilton, Jasper Kok, Michael Sigl, Jordan Abell, Adwoa Aboagye-Okyere, Joe Adabouk Amooli, Samuel Albani, Susanne Bauer, Emilie Beaudon, Hunter Brown, Nathan Chellman, Nicolás Cosentino, Nathalie Goodkin, Christopher Guiterman, Stijn Hantson, Chengfei He, Aviva Intveld, Jed Kaplan, Jeremy Klavans, Fabrice Lambert, Haobo Liu, Marie-France Loutre, Joe McConnell, Zachary McGraw, Keren Mezuman, Ron Miller, Nicholas O’Mara, Maria Rosabelle Ong, Gavin Schmidt, Richard Vachula, Lily Wu, and Bingqing Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2026-4532, https://doi.org/10.5194/egusphere-2026-4532, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Aerosols are poorly known in past climates, and yet it is very important to understand how aerosols are changing in different climates. In this paper we review available proxy data and modeling approaches to characterize aerosols in past climates. In addition, we propose future studies that can help improve our understanding.
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathan Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Medeiros, Enrico Scoccimarro, Jeremy Walton, Phil Kershaw, André Lanfer Marquez, Malcolm J. Roberts, Eleanor O'Rourke, Beth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
Geosci. Model Dev., 19, 7415–7455, https://doi.org/10.5194/gmd-19-7415-2026, https://doi.org/10.5194/gmd-19-7415-2026, 2026
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The Rapid Evaluation Framework (REF) is a community-driven platform for benchmarking and performance assessment of Earth system models. Built upon four disparate community evaluation tools, the REF is designed to provide model-data comparisons for the Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project. The REF will be run at the Earth System Grid Federation to enable model devleopers and scientists to quickly identify model biases and performance issues.
Noah Liguori-Bills, Catherine E. Scott, Ken S. Carslaw, Natalie Kehrwald, Stijn Hantson, Susan Kaspari, Carlo Barbante, Elena Barbaro, Paolo Gabrielli, Roberta Zangrando, Lonnie G. Thompson, and Douglas S. Hamilton
EGUsphere, https://doi.org/10.5194/egusphere-2026-2728, https://doi.org/10.5194/egusphere-2026-2728, 2026
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Ice cores preserve changes in landscape fires and human-caused combustion. In this study, we compared ice core data from every continent, except Oceania, to computer model simulations of fire. We found a large disagreement in the 1850 CE to 1980 CE black carbon ratio. After exploring changes in emissions, transport, and aerosol microphysical processes as potential reasons for this disagreement, our results suggested that fire emission input datasets for climate models are the primary cause.
Chantelle Burton, Francesca Di Giuseppe, Matthew W. Jones, Douglas I. Kelley, Maria L. F. Barbosa, Joe McNorton, Robert Potts, Carlota Segura-Garcia, John T. Abatzoglou, Iulian Alin Rosu, Niels Andela, Liana O. Anderson, Sally Archibald, Esther Brambleby, Emilio Chuvieco, Andy Ciavarella, Hamish Clarke, Francisco de la Barrera, Carlos M. Di Bella, Enza Di Tomaso, Kebonye Dintwe, Tim S. Doherty, Victoria M. Donovan, Jonathan M. Eden, Paulo M. Fernandes, Lukas Fiedler, Louis Giglio, Olivia Haas, Douglas Hamilton, Stijn Hantson, Sarah Harris, Andrew J. Hartley, Theodore R. Keeping, Crystal A. Kolden, Jean-Luc Kouassi, Elena Kukavskaya, Seppe Lampe, Zhongwei Liu, Guilherme Mataveli, Sarah Meier, Duarte Oom, Mark Parrington, Yuquan Qu, Victor Resco de Dios, Julien Ruffault, Mojtaba Sadegh, Cristina Santín, Fernando Sedano, Jacquelyn K. Shuman, Patrícia S. Silva, Fiona R. Spuler, Carmen B. Steinmann, Veerachai Tanpipat, Miguel Ángel Torres-Vazquez, Marco Turco, Guido R. van der Werf, Dave van Wees, Sander Veraverbeke, Jakob B. Wessel, and Bo Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-587, https://doi.org/10.5194/essd-2026-587, 2026
Revised manuscript under review for ESSD
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The third State of Wildfires report examines extreme wildfire events from 2025 to early 2026. It analyses key regional events in Midwestern Canadian Shield Forests, Northwest Iberia, and Chilean Temperate Forests and Matorral, assessing their impacts, drivers, and attributing them to climate change. Climate change greatly increased the likelihood of these fires, and without strong mitigation, such events will become more frequent.
Matheus de Almeida, Charles M. Shobe, Duna C. Roda-Boluda, Loraine Gourbet, Amber Distelbrink, Sander Veraverbeke, and Benjamin Campforts
EGUsphere, https://doi.org/10.5194/egusphere-2026-3521, https://doi.org/10.5194/egusphere-2026-3521, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Fires play an important control on changing Earth surface processes across a wide range of landscapes. Understanding post-fire sediment dynamics is important to predict the Earth's surface response to fires in landscapes facing environmental changes, as changing fire regimes due to climate variations may have a large impact on soil storage. We develop FireLands, a new landscape evolution model that provides a toolbox to explore the effects of fires on sediment transport over several timescales.
A. Park Williams, John T. Abatzoglou, Gavin D. Madakumbura, Haibo Liu, Stefan Rahimi, and Christopher Daly
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-391, https://doi.org/10.5194/essd-2026-391, 2026
Preprint under review for ESSD
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Here we introduce ParallelClim-WestUS-Daily, a new dataset of daily gridded climate data for the western US from 1951–2025 as well as a parallel, counterfactual realization of the observed climate but without human-caused climate change. This dataset will enable assessments of how climate change has affected complex hydroclimatic processes such as hydrology, vegetation dynamics, and wildfire.
Jessica Stacey, Richard A. Betts, Andrew Hartley, Lina M. Mercado, and Nicola Gedney
Hydrol. Earth Syst. Sci., 30, 4225–4243, https://doi.org/10.5194/hess-30-4225-2026, https://doi.org/10.5194/hess-30-4225-2026, 2026
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Plants typically transpire less with rising atmospheric carbon dioxide, leaving more water in the ground for human use, but many future water scarcity assessments ignore this effect. We use a land surface model to examine how plant responses to carbon dioxide and climate change affect future water scarcity. Our results suggest that including these plant responses increases overall water availability for most people, highlighting the importance of their inclusion in future water scarcity studies.
Rebecca M. Varney, Daniel Hooke, Norman J. Steinert, T. Luke Smallman, Camilla Mathison, and Eleanor J. Burke
Earth Syst. Dynam., 17, 913–928, https://doi.org/10.5194/esd-17-913-2026, https://doi.org/10.5194/esd-17-913-2026, 2026
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The northern high latitudes mitigate climate change by land ecosystems absorbing more carbon from the atmosphere than they release. This carbon sink is sensitive to long-term CO2 emissions. Here, we use a probabilistic framework to quantify the timing and magnitude of a transition to a carbon source in different future emission scenarios, including overshoot. The fate of this region is dependent on the balance between carbon loss from permafrost and gain from increased vegetation productivity.
Rui Li, Haley E. Plaas, Yifan Zhang, Yizhu Chen, Tianyu Zhang, Yi Yang, Sagar Rathod, Guohua Zhang, Xinming Wang, Douglas S. Hamilton, and Mingjin Tang
Atmos. Chem. Phys., 26, 9037–9060, https://doi.org/10.5194/acp-26-9037-2026, https://doi.org/10.5194/acp-26-9037-2026, 2026
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This work measured solubility of aerosol Fe from several distinct anthropogenic sources, updated aerosol Fe solubility parameterizations used in the Community Earth System model, and found that residential burning is a significant source of soluble aerosol Fe to the ocean.
João C. M. Teixeira, Chantelle Burton, Douglas I. Kelley, Gerd A. Folberth, Fiona M. O'Connor, Richard A. Betts, and Apostolos Voulgarakis
Earth Syst. Dynam., 17, 739–767, https://doi.org/10.5194/esd-17-739-2026, https://doi.org/10.5194/esd-17-739-2026, 2026
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Burned area has declined globally since the late 1990s, especially in tropical savannas, yet many climate models miss this trend because they poorly represent human fire use and suppression. We tested whether adding a simple link to human development improves a fire model. This reduced large regional errors and better captured downward trends in several areas, though it increased global underestimation and reduced variability. Human influence is key, but simple assumptions have trade-offs.
Piers M. Forster, Tristram Walsh, Chris Smith, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Robbie M. Andrew, Chris Atkinson, Richard A. Betts, Antonio Bombelli, Samantha N. Burgess, Lijing Cheng, Helen E. Claxton, Pierre Friedlingstein, Thomas L. Frölicher, Catia M. Domingues, Thomas Gasser, Catherine H. Gregory, Rachel M. Hoesly, Daniel Huppmann, Masayoshi Ishii, Christopher Kadow, Alexia Karwat, John Kennedy, Rachel E. Killick, Mahesh V. M. Kovilakam, Paul B. Krummel, Xin Lan, Jean-François Lamarque, Aurélien Liné, Belén Martín-Míguez, Didier P. Monselesan, Colin Morice, Jens Mühle, Pino Mussak, Glen P. Peters, Anna Pirani, Julia Pongratz, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Steven J. Smith, Ghassan Taha, Caterina Tassone, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Marco Zecchetto, Junting Zhong, Xiao-Ye Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, https://doi.org/10.5194/essd-18-3889-2026, 2026
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We give our annual update of key climate indicators. Our work quantifies the human contribution to global warming and the pace of climate change. This represents a large effort by the international community akin to an Intergovernmental Panel on Climate Change (IPCC) report.
Andreia F. S. Ribeiro, Maik Biling, Kirsten Thonicke, Werner von Bloh, Jakob Wessel, Sabine Undorf, Matthias Forkel, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2026-2952, https://doi.org/10.5194/egusphere-2026-2952, 2026
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Wildfires are becoming more extreme, yet our state-of-the-art tools fail to capture the full risk. We simulate a large ensemble of wildfire simulations capturing a broader range of physically plausible extreme wildfire events beyond what observations alone can reveal. Extreme fire danger alone does not explain the worst impacts: ignitions, fuel and vegetation-fire feedback need to be incorporated. This modelling framework is transferable to other climate-impact sectors beyond wildfires.
Ni Li, Wim Thiery, Shorouq Zahra, Mariana Madruga de Brito, Koffi Worou, Murathan Kurfalı, Seppe Lampe, Paul Muñoz, Clare Flynn, Camila Trigoso, Joakim Nivre, Jakob Zscheischler, and Gabriele Messori
Nat. Hazards Earth Syst. Sci., 26, 2609–2636, https://doi.org/10.5194/nhess-26-2609-2026, https://doi.org/10.5194/nhess-26-2609-2026, 2026
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Climate extremes threaten society and ecosystems, making impact understanding critical. Wikimpacts 1.0 provides an automated pipeline processing Wikipedia texts with underexploited information on climate impacts, yielding comprehensive socio-economic impact data for 2726 climate events from 1034–2024. It offers broader storm-related impacts and finer spatial resolution than established databases, showcasing natural language processing's potential to advance climate impact data.
Michael Gregory Windisch, Yann Quilcaille, Camilla Mathison, Claudia Tebaldi, Eleanor Burke, Laila Gohar, Chris Smith, Sarah Schöngart, Abigail Snyder, Siddarth Durga, Kalyn Dorheim, and Sonia Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2026-2253, https://doi.org/10.5194/egusphere-2026-2253, 2026
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Creating consistent climate scenarios remains challenging. The computational cost of comprehensive climate models leaves most scenarios without spatial climate outcomes, limiting feedback between climate consequences and scenario assumptions. We apply three spatial emulators to test their potential and current limitations in rapidly translating scenarios into spatial outcomes to identify regional risks, fill gaps in scenario coverage, and feed climate consequences back into scenario assumptions.
Katja Frieler, Stefan Lange, Jacob Schewe, Matthias Mengel, Simon Treu, Christian Otto, Jan Volkholz, Christopher P. O. Reyer, Stefanie Heinicke, Colin Jones, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Ryan Heneghan, Derek P. Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Dánnell Quesada-Chacón, Kerry Emanuel, Chia-Ying Lee, Suzana J. Camargo, Linn Hamester, Jonas Jägermeyr, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Lisa Novak, Inga J. Sauer, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala, Matthew Forrest, Michel Bechtold, Robert Reinecke, Inge de Graaf, Jed O. Kaplan, Alexander Koch, Matthieu Lengaigne, Rohini Kumar, and Maryna Strokal
Geosci. Model Dev., 19, 4095–4135, https://doi.org/10.5194/gmd-19-4095-2026, https://doi.org/10.5194/gmd-19-4095-2026, 2026
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This paper describes the experiments and data sets necessary to run historic and future impact projections, and the underlying assumptions of future climate change as defined by the 3rd round of the ISIMIP Project (Inter-sectoral Impactmodel Intercomparison Project, isimip.org). ISIMIP provides a framework for cross-sectorally consistent climate impact simulations to contribute to a comprehensive and consistent picture of the world under different climate-change scenarios.
Elizabeth Quaye, Ben T. Johnson, James M. Haywood, Guido R. van der Werf, Roland Vernooij, Stephen A. Sitch, and Tom Eames
Atmos. Chem. Phys., 26, 6629–6654, https://doi.org/10.5194/acp-26-6629-2026, https://doi.org/10.5194/acp-26-6629-2026, 2026
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We find aerosol optical depths in a global climate model are overestimated during extreme wildfire events if emissions are scaled up by a factor of two, typically applied to improve simulated aerosol on seasonal–annual timescales. We propose a technique where a variable scaling factor is determined by fuel consumption, improving correlation in five fire-affected areas. We explore the impact of this change on aerosol radiative effects, during extreme events and on broader space and time scales.
Fang Li, David M. Lawrence, Brendan M. Rogers, Chantelle Burton, Huilin Huang, Yiquan Jiang, Johannes W. Kaiser, Matthew Kasoar, Hanna Lee, Ruby Leung, Lars Nieradzik, Aihui Wang, Daniel S. Ward, Ligeer Ce, Yangchun Li, Zhongda Lin, Apostolos Voulgarakis, and Yongkang Xue
Geosci. Model Dev., 19, 3989–4007, https://doi.org/10.5194/gmd-19-3989-2026, https://doi.org/10.5194/gmd-19-3989-2026, 2026
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Extreme fire events are increasing, and fires are projected to rise across most regions, posing growing risks to ecosystems and society. As a key Earth system process, fire is now modeled in most Earth System Models (ESMs). FireMIP (Fire Modeling Intercomparison Project) within CMIP7 will evaluate fire simulations in state‑of‑the‑art ESMs, project future fire changes, and provide quantitative, process‑based understanding of fire's role in the Earth system.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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The Global Carbon Budget 2025 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2025). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Erika Solano-Romero, Carlota Segura-Garcia, M. Lucrecia Pettinari, Amin Khairoun, Miguel Ángel Torres-Vázquez, and Emilio Chuvieco
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-236, https://doi.org/10.5194/essd-2026-236, 2026
Revised manuscript under review for ESSD
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To better understand where and when the world’s most unusual fires occur, we created the first global database of extreme fire events for 2003 to 2022. Using satellite observations of burned land and fire energy, we identified 19,951 extreme events and found clear differences across regions and seasons. This new resource can help researchers and decision makers improve studies of climate, ecosystems, and future fire risk.
Jakob Benjamin Wessel and Richard E. Chandler
Adv. Stat. Clim. Meteorol. Oceanogr., 12, 149–172, https://doi.org/10.5194/ascmo-12-149-2026, https://doi.org/10.5194/ascmo-12-149-2026, 2026
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Precipitation generators are statistical models for generating long synthetic sequences of (multisite) precipitation for hydrological analyses. One widely-used class of precipitation generators is based on so-called 'generalised linear models'. In this work, we extend this class to better capture key features of daily precipitation and introduce a new method to ensure realistic inter-site dependence, so neighbouring locations tend to be dry or wet at the same time.
Derrick Muheki, Bas Vercruysse, Krishna Kumar Thirukokaranam Chandrasekar, Christophe Verbruggen, Julie M. Birkholz, Koen Hufkens, Hans Verbeeck, Pascal Boeckx, Seppe Lampe, Ed Hawkins, Peter Thorne, Dominique Kankonde Ntumba, Olivier Kapalay Moulasa, and Wim Thiery
Geosci. Model Dev., 19, 3213–3255, https://doi.org/10.5194/gmd-19-3213-2026, https://doi.org/10.5194/gmd-19-3213-2026, 2026
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Archives worldwide host vast records of observed weather data crucial for understanding climate variability. However, most of these records are still in paper form, limiting their use. To address this, we developed MeteoSaver, an open-source tool, to transcribe these records to machine-readable format. Applied to ten handwritten temperature sheets, it achieved a median accuracy of 74 %. This tool offers a promising solution to preserve records from archives and unlock historical weather insights.
Sasha Roewer, Lukas Fiedler, Marius Årthun, Willem Huiskamp, and Stefan Rahmstorf
Ocean Sci., 22, 1195–1211, https://doi.org/10.5194/os-22-1195-2026, https://doi.org/10.5194/os-22-1195-2026, 2026
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The Atlantic Meridional Overturning Circulation (AMOC) is weakening in response to global warming, while the Nordic Seas Overturning Circulation (NOC) is projected to strengthen. We suggest a feedback mechanism in which a weakened AMOC leads to reduced salt transport into the North Atlantic, decreasing the density in that region and potentially strengthening the NOC.
William F. Lamb, Robbie M. Andrew, Matthew Jones, Zebedee Nicholls, Glen P. Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven J. Smith, Francesco N. Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers M. Forster
Earth Syst. Sci. Data, 18, 2549–2572, https://doi.org/10.5194/essd-18-2549-2026, https://doi.org/10.5194/essd-18-2549-2026, 2026
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This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
Ehsan Modiri, Oldrich Rakovec, Pallav Kumar Shrestha, Almudena García-García, Leandro Avila, Katie Blackford, Elizabeth Cooper, Bram Droppers, Paolo Filippucci, Milan Fischer, Matěj Orság, Pietro Stradiotti, Luca Brocca, Douglas B. Clark, Wouter Dorigo, Stefan Kollet, Jian Peng, Niko Wanders, and Luis Samaniego
EGUsphere, https://doi.org/10.5194/egusphere-2026-1012, https://doi.org/10.5194/egusphere-2026-1012, 2026
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Drought impacts water supply, agriculture, and ecosystems, yet hydrological models often disagree on when and where drought occurs. This study tested whether satellite observations can improve how models represent soil moisture drought in the Rhine River basin. Using several models and major drought events, we show that satellite data improve spatial realism and reveal important differences among models, helping to better understand uncertainty in drought monitoring and early warning.
Tim Butler, Tabish Ansari, Claudio A. Belis, Elisa Bergas-Masso, Willem van Caspel, Hilde Fagerli, Johannes Flemming, Marta Garcia Vivanco, Paul Griffiths, Douglas S. Hamilton, Coralina Hernandez Trujillo, Lena Höglund-Isaksson, Vincent Huijnen, Matthew Kasoar, Johannes W. Kaiser, Gerbrand Koren, Zbigniew Klimont, Florian Lindl, Aura Lupascu, Mariano Mertens, Martijn Schaap, Steven T. Turnock, Oliver Wild, Philipp Weiss, Jacek Kaminski, Rosa Wu, and Terry Keating
EGUsphere, https://doi.org/10.5194/egusphere-2026-1367, https://doi.org/10.5194/egusphere-2026-1367, 2026
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Air pollution travels across continents, meaning emissions in one region can affect air quality far away. To better understand this, scientists from many groups are planning to run coordinated computer simulations of the atmosphere. By comparing results across models and emission scenarios, the planned study will show how pollution moves between regions and which sources matter most, helping governments design more effective air quality policies.
Martin Willett, Melissa Brooks, Andrew Bushell, Paul Earnshaw, Samantha Smith, Lorenzo Tomassini, Martin Best, Ian Boutle, Jennifer Brooke, John M. Edwards, Andrew D. Elvidge, Kalli Furtado, Catherine Hardacre, Andrew J. Hartley, Alan J. Hewitt, Ben Johnson, Adrian Lock, Andy Malcolm, Jane Mulcahy, Eike Müller, Ian A. Renfrew, Heather Rumbold, Gabriel G. Rooney, Alistair Sellar, Masashi Ujiie, Annelize van Niekerk, Andy Wiltshire, and Michael Whitall
Geosci. Model Dev., 19, 1473–1517, https://doi.org/10.5194/gmd-19-1473-2026, https://doi.org/10.5194/gmd-19-1473-2026, 2026
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of Joint UK Land Environment Simulator (JULES) are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA8GL9, which includes improvements to the representation of convection and other physical processes. GA8GL9 is used for operational weather prediction in the UK and forms the basis for the next GA and GL configuration.
Maria P. Velásquez-García, Richard J. Pope, Steven T. Turnock, Chetan Deva, David P. Moore, Guilherme Mataveli, Steve R. Arnold, Ruth M. Doherty, and Martyn P. Chipperfield
Biogeosciences, 23, 1341–1364, https://doi.org/10.5194/bg-23-1341-2026, https://doi.org/10.5194/bg-23-1341-2026, 2026
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Incorporating fire simulation into climate models is crucial for accurately representing interactions between fires, ecosystems, and climate, thereby enhancing climate projections. In South America, the INFERNO (Interactive Fires and Emissions algorithm for Natural Environments) fire model broadly captures CO emissions in active fire zones, e.g., the Amazon Arc of Deforestation. Still, it tends to overestimate emissions in tree-rich ecosystems, where INFERNO is too sensitive to low soil moisture, and to underestimate emissions in less tree-abundant ecosystems.
A. Park Williams, Winslow D. Hansen, Caroline S. Juang, John T. Abatzoglou, Volker C. Radeloff, Bowen Wang, Jazlynn Hall, Jatan Buch, and Gavin D. Madakumbura
Geosci. Model Dev., 19, 1157–1191, https://doi.org/10.5194/gmd-19-1157-2026, https://doi.org/10.5194/gmd-19-1157-2026, 2026
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The new Western United States Large Forest Fire Stochastic Simulator (WULFFSS) is a monthly gridded model to simulate forest fires across the western United States in response to vegetation, topographic, anthropogenic, and climate factors. The model is highly skillful, accounting for over 80 % of the observed variability in annual forest-fire area and capturing observed spatial, intra-annual variations, and trends.
Seppe Lampe, Lukas Gudmundsson, Basil Kraft, Stijn Hantson, Douglas Kelley, Vincent Humphrey, Bertrand Le Saux, Emilio Chuvieco, and Wim Thiery
Geosci. Model Dev., 19, 955–988, https://doi.org/10.5194/gmd-19-955-2026, https://doi.org/10.5194/gmd-19-955-2026, 2026
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We introduce BuRNN (BUrned area modelling by Recurrent Neural Networks), a model which estimates monthly burned area based on satellite observations and climate, vegetation, and socio-economic data using machine learning. BuRNN outperforms existing process-based fire models, which improves our capabilities of modelling past and future burned areas.
Claudia Di Biagio, Elisa Bru, Avila Orta, Servanne Chevaillier, Clarissa Baldo, Antonin Bergé, Mathieu Cazaunau, Sandra Lafon, Sophie Nowak, Edouard Pangui, Meinrat O. Andreae, Pavla Dagsson-Waldhauserova, Kebonyethata Dintwe, Konrad Kandler, James S. King, Amelie Chaput, Gregory S. Okin, Stuart Piketh, Thuraya Saeed, David Seibert, Zongbo Shi, Earle Williams, Pasquale Sellitto, and Paola Formenti
Atmos. Chem. Phys., 26, 1079–1091, https://doi.org/10.5194/acp-26-1079-2026, https://doi.org/10.5194/acp-26-1079-2026, 2026
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Spectroscopy measurements show that the absorbance of dust in the far-infrared up to 25 µm is comparable in intensity to that in the mid-infrared (3–15 µm) suggesting possible relevance for its direct radiative effect. Absorption signatures differ between Icelandic and low/mid-latitude dust due to differences in mineralogical composition. Spectral differences could be used to characterise the mineralogy and trace the origin of airborne dust based on infrared remote sensing observations.
Tom Eames, Nick Schutgens, Eleftherios Ioannidis, Ivar R. van der Velde, Max J. van Gerrevink, Roland Vernooij, and Guido R. van der Werf
Atmos. Chem. Phys., 25, 17429–17453, https://doi.org/10.5194/acp-25-17429-2025, https://doi.org/10.5194/acp-25-17429-2025, 2025
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Prescribed burning is used as a landscape management tool in southern African savannas. By deliberately changing the timing of fires in this region, the climate effect (radiative forcing) of a fire season can be altered. We show that by burning earlier in the dry season a small climate cooling effect can be achieved, similar to that of a 10 % reduction in global commercial aviation emissions. Local effects must be considered before implementing a fire regime shift for climate change mitigation.
Pere Joan Gelabert, Adrián Jiménez-Ruano, Clara Ochoa, Fermín Alcasena, Johan Sjöström, Christopher Marrs, Luís Mário Ribeiro, Palaiologos Palaiologou, Carmen Bentué Martínez, Emilio Chuvieco, Cristina Vega-García, and Marcos Rodrigues
Nat. Hazards Earth Syst. Sci., 25, 4713–4729, https://doi.org/10.5194/nhess-25-4713-2025, https://doi.org/10.5194/nhess-25-4713-2025, 2025
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Wildfires threaten ecosystems and communities across Europe. Our study developed models to predict where and why these ignitions occur in different European environments. We found that weather anomalies and human factors, like proximity to urban areas and roads, are key drivers. Using Machine Learning our models achieved strong predictive accuracy. These insights help design better wildfire prevention strategies, ensuring safer landscapes and communities as fire risks grow with climate change.
Clément Bourgoin, René Beuchle, Alfredo Branco, João Carreiras, Guido Ceccherini, Duarte Oom, Jesus San-Miguel-Ayanz, and Fernando Sedano
Biogeosciences, 22, 5247–5256, https://doi.org/10.5194/bg-22-5247-2025, https://doi.org/10.5194/bg-22-5247-2025, 2025
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The Amazon forest faces increasing wildfires due to extreme drought and human activity. In 2024, disturbances surged by 152 %, hitting a 20-year high. Forest degradation from fires grew by over 400 %, exceeding that from deforestation. Brazil and Bolivia were hit hardest. These fires released huge amounts of CO2, 7 times more than in recent years, pushing the Amazon towards a dangerous tipping point. Urgent action is needed to prevent irreversible harm.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frédérik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilaria D'Elia, Massimo D'Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
Geosci. Model Dev., 18, 6835–6883, https://doi.org/10.5194/gmd-18-6835-2025, https://doi.org/10.5194/gmd-18-6835-2025, 2025
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The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The service relies on a distributed modelling production by 11 leading European modelling teams following stringent requirements with an operational design that has no equivalent in the world. All the products are free, open, and quality-assured and disseminated with a high level of reliability.
Kirsty J. Pringle, Richard Rigby, Steven T. Turnock, Carly L. Reddington, Meruyert Shayakhmetova, Malcolm Illingworth, Denis Barclay, Neil Chue Hong, Ed Hawkins, Douglas S. Hamilton, Ethan Brain, and James B. McQuaid
Geosci. Commun., 8, 229–236, https://doi.org/10.5194/gc-8-229-2025, https://doi.org/10.5194/gc-8-229-2025, 2025
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The Air Quality Stripes images visualise historical changes in particulate matter air pollution in over 150 cities worldwide. The project celebrates significant improvements in air quality in regions like Europe, North America, and China while highlighting the urgent need for action in areas such as central Asia. Designed to raise awareness, the images aim to inspire discussions about the critical impact of air pollution and the global inequalities it causes.
Fiona R. Spuler, Marlene Kretschmer, Magdalena Alonso Balmaseda, Yevgeniya Kovalchuk, and Theodore G. Shepherd
Weather Clim. Dynam., 6, 995–1014, https://doi.org/10.5194/wcd-6-995-2025, https://doi.org/10.5194/wcd-6-995-2025, 2025
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Large-scale atmospheric dynamics modulate the occurrence of extreme events and can improve their prediction. We present a generative machine learning method to identify key dynamical drivers of an impact variable in the form of targeted circulation regimes. Applied to extreme precipitation in Morocco, we show that these targeted regimes are more predictive of the impact while preserving their own predictability and physical consistency.
Renata Moura da Veiga, Celso von Randow, Chantelle Burton, Douglas I. Kelley, Manoel Cardoso, and Fabiano Morelli
Nat. Hazards Earth Syst. Sci., 25, 3581–3601, https://doi.org/10.5194/nhess-25-3581-2025, https://doi.org/10.5194/nhess-25-3581-2025, 2025
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We systematically reviewed 77 papers to understand the Cerrado’s fire emissions within the global carbon budget by evaluating how fire parameters can inform emission estimates and mitigation strategies. Estimating fire emissions in the Cerrado requires a holistic approach, combining fire carbon emission estimates, fire dynamic parameters, and fire management and policy. We highlight key research gaps that could provide more comprehensive insights into accounting for fire emissions in the Cerrado.
Anastasios Rovithakis, Eleanor Burke, Chantelle Burton, Matthew Kasoar, Manolis G. Grillakis, Konstantinos D. Seiradakis, and Apostolos Voulgarakis
Nat. Hazards Earth Syst. Sci., 25, 3185–3200, https://doi.org/10.5194/nhess-25-3185-2025, https://doi.org/10.5194/nhess-25-3185-2025, 2025
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We used a land surface computer model to forecast how climate change will impact wildfires in Greece. Our results show a significant increase in future burnt area due to hotter, drier climate. Allowing vegetation to change with the climate lessens this increase overall, since fire is no longer igniting in areas already burnt, and it even led to projected decreases in the agricultural areas in the north of the country.
Emmanouil Proestakis, Vassilis Amiridis, Carlos Pérez García-Pando, Svetlana Tsyro, Jan Griesfeller, Antonis Gkikas, Thanasis Georgiou, María Gonçalves Ageitos, Jeronimo Escribano, Stelios Myriokefalitakis, Elisa Bergas Masso, Enza Di Tomaso, Sara Basart, Jan-Berend W. Stuut, and Angela Benedetti
Earth Syst. Sci. Data, 17, 4351–4395, https://doi.org/10.5194/essd-17-4351-2025, https://doi.org/10.5194/essd-17-4351-2025, 2025
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Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established based on Earth observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light on physical processes related to the dust cycle, and improving the understanding of dust biogeochemical impacts on oceanic ecosystems, weather, and climate.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
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To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025, https://doi.org/10.5194/essd-17-2887-2025, 2025
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Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a dataset of permafrost thaw depth measurements from burned and unburned sites contributed by researchers from across the northern high-latitude region. We estimated maximum thaw depth for each measurement, which addresses a key challenge: the ability to assess impacts of wildfire on maximum thaw depth when measurement timing varies.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid T. Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
Atmos. Chem. Phys., 25, 6219–6255, https://doi.org/10.5194/acp-25-6219-2025, https://doi.org/10.5194/acp-25-6219-2025, 2025
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This study uses dry CO2 mole fractions from the Amazon Tall Tower Observatory together with airborne profiles to estimate net carbon exchange in tropical South America. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. Finally, to further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon–Andes foothills.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
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In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Maria Lucia Ferreira Barbosa, Douglas I. Kelley, Chantelle A. Burton, Igor J. M. Ferreira, Renata Moura da Veiga, Anna Bradley, Paulo Guilherme Molin, and Liana O. Anderson
Geosci. Model Dev., 18, 3533–3557, https://doi.org/10.5194/gmd-18-3533-2025, https://doi.org/10.5194/gmd-18-3533-2025, 2025
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As fire seasons in Brazil become increasingly severe, confidently understanding the factors driving fires is more critical than ever. To address this challenge, we developed FLAME (Fire Landscape Analysis using Maximum Entropy), a new model designed to predict fires and to analyse the spatial influence of both environmental and human factors while accounting for uncertainties. By adapting the model to different regions, we can enhance fire management strategies, making FLAME a powerful tool for protecting landscapes in Brazil and beyond.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Joseph W. Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci., 25, 1521–1541, https://doi.org/10.5194/nhess-25-1521-2025, https://doi.org/10.5194/nhess-25-1521-2025, 2025
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In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought stress on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) in Brazil. This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Paulo M. Fernandes, Nuno G. Guiomar, and Ana Sá
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-587, https://doi.org/10.5194/essd-2024-587, 2025
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Mapping vegetation as fuel is important for understanding and managing wildfires. Aragoneses et al. (2023) created a European fuel map, but their method has flaws. The fuel types don’t match real fire behavior, and key vegetation metrics were mapped using unreliable methods. The map’s low detail and oversimplified approach caused it to overestimate fire risk in areas with less flammable vegetation, limiting its usefulness for wildfire research and planning.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Müller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul A. Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
Biogeosciences, 22, 323–340, https://doi.org/10.5194/bg-22-323-2025, https://doi.org/10.5194/bg-22-323-2025, 2025
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in northern Europe using ecosystem models, atmospheric inversions, and upscaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions, and upscaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Raphaël d'Andrimont, Momchil Yordanov, Fernando Sedano, Astrid Verhegghen, Peter Strobl, Savvas Zachariadis, Flavia Camilleri, Alessandra Palmieri, Beatrice Eiselt, Jose Miguel Rubio Iglesias, and Marijn van der Velde
Earth Syst. Sci. Data, 16, 5723–5735, https://doi.org/10.5194/essd-16-5723-2024, https://doi.org/10.5194/essd-16-5723-2024, 2024
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The Land Use/Cover Area frame Survey (LUCAS) Copernicus 2022 is a large and systematic in situ field survey of 137 966 polygons over the European Union in 2022. The data contain 82 land cover classes and 40 land use classes.
Lucas R. Diaz, Clement J. F. Delcourt, Moritz Langer, Michael M. Loranty, Brendan M. Rogers, Rebecca C. Scholten, Tatiana A. Shestakova, Anna C. Talucci, Jorien E. Vonk, Sonam Wangchuk, and Sander Veraverbeke
Earth Syst. Dynam., 15, 1459–1482, https://doi.org/10.5194/esd-15-1459-2024, https://doi.org/10.5194/esd-15-1459-2024, 2024
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Our study in eastern Siberia investigated how fires affect permafrost thaw depth in larch forests. We found that fire induces deeper thaw, yet this process was mediated by topography and vegetation. By combining field and satellite data, we estimated summer thaw depth across an entire fire scar. This research provides insights into post-fire permafrost dynamics and the use of satellite data for mapping fire-induced permafrost thaw.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
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This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
Bhupinderjeet Singh, Mingliang Liu, John Abatzoglou, Jennifer Adam, and Kirti Rajagopalan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2284, https://doi.org/10.5194/egusphere-2024-2284, 2024
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Hydrology models rely on simplistic static approaches to precipitation phase partitioning. We evaluate model skill changes for a suite of snow metrics by transitioning to a more accurate dynamic partitioning. We found that the transition resulted in a better match between modeled and observed metrics, with a 50 % reduction in model bias, emphasizing the need for the hydrological modeling community to adopt dynamic partitioning.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
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This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
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Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Julia Kelly, Stefan H. Doerr, Johan Ekroos, Theresa S. Ibáñez, Md. Rafikul Islam, Cristina Santín, Margarida Soares, and Natascha Kljun
EGUsphere, https://doi.org/10.5194/egusphere-2024-2016, https://doi.org/10.5194/egusphere-2024-2016, 2024
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We measured soil carbon fluxes during the first four years after a wildfire in the Swedish boreal forest. Soil CO2 emissions decreased substantially only when trees were killed by fire or by post-fire logging, but not when trees survived the fire and were left standing. Soil methane flux was not affected by fire. Logging trees already killed by fire had no additional impact on soil carbon fluxes. Post-fire forest management strategy impacted vegetation regrowth and carbon dynamics.
Yavar Pourmohamad, John T. Abatzoglou, Erin J. Belval, Erica Fleishman, Karen Short, Matthew C. Reeves, Nicholas Nauslar, Philip E. Higuera, Eric Henderson, Sawyer Ball, Amir AghaKouchak, Jeffrey P. Prestemon, Julia Olszewski, and Mojtaba Sadegh
Earth Syst. Sci. Data, 16, 3045–3060, https://doi.org/10.5194/essd-16-3045-2024, https://doi.org/10.5194/essd-16-3045-2024, 2024
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The FPA FOD-Attributes dataset provides > 300 biological, physical, social, and administrative attributes associated with > 2.3×106 wildfire incidents across the US from 1992 to 2020. The dataset can be used to (1) answer numerous questions about the covariates associated with human- and lightning-caused wildfires and (2) support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
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Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Adrianus de Laat, Vincent Huijnen, Niels Andela, and Matthias Forkel
EGUsphere, https://doi.org/10.5194/egusphere-2024-732, https://doi.org/10.5194/egusphere-2024-732, 2024
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This study assesses state-of-the art and more advanced and innovative satellite-observation-based (bottom-up) wildfire emission estimates. They are evaluated by comparison with satellite observation of single fire emission plumes. Results indicate that more advanced fire emission estimates – more information – are more realistic but that especially for a limited number of very large fires certain differences remain – for unknown reasons.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
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With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
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Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Xiaoxia Shang, Antti Lipponen, Maria Filioglou, Anu-Maija Sundström, Mark Parrington, Virginie Buchard, Anton S. Darmenov, Ellsworth J. Welton, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Alejandro Rodríguez-Gómez, Mika Komppula, and Tero Mielonen
Atmos. Chem. Phys., 24, 1329–1344, https://doi.org/10.5194/acp-24-1329-2024, https://doi.org/10.5194/acp-24-1329-2024, 2024
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In June 2019, smoke particles from a Canadian wildfire event were transported to Europe. The long-range-transported smoke plumes were monitored with a spaceborne lidar and reanalysis models. Based on the aerosol mass concentrations estimated from the observations, the reanalysis models had difficulties in reproducing the amount and location of the smoke aerosols during the transport event. Consequently, more spaceborne lidar missions are needed for reliable monitoring of aerosol plumes.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Thomas D. Hessilt, Brendan M. Rogers, Rebecca C. Scholten, Stefano Potter, Thomas A. J. Janssen, and Sander Veraverbeke
Biogeosciences, 21, 109–129, https://doi.org/10.5194/bg-21-109-2024, https://doi.org/10.5194/bg-21-109-2024, 2024
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In boreal North America, snow and frozen ground prevail in winter, while fires occur in summer. Over the last 20 years, the northwestern parts have experienced earlier snow disappearance and more ignitions. This is opposite to the southeastern parts. However, earlier ignitions following earlier snow disappearance timing led to larger fires across the region. Snow disappearance timing may be a good proxy for ignition timing and may also influence important atmospheric conditions related to fires.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
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We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
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Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Roland Vernooij, Tom Eames, Jeremy Russell-Smith, Cameron Yates, Robin Beatty, Jay Evans, Andrew Edwards, Natasha Ribeiro, Martin Wooster, Tercia Strydom, Marcos Vinicius Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, Dave van Wees, and Guido R. Van der Werf
Earth Syst. Dynam., 14, 1039–1064, https://doi.org/10.5194/esd-14-1039-2023, https://doi.org/10.5194/esd-14-1039-2023, 2023
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Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO2, CO, CH4, and N2O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Sebastien Garrigues, Melanie Ades, Samuel Remy, Johannes Flemming, Zak Kipling, Istvan Laszlo, Mark Parrington, Antje Inness, Roberto Ribas, Luke Jones, Richard Engelen, and Vincent-Henri Peuch
Atmos. Chem. Phys., 23, 10473–10487, https://doi.org/10.5194/acp-23-10473-2023, https://doi.org/10.5194/acp-23-10473-2023, 2023
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating the assimilation of the NOAA VIIRS AOD product in the ECMWF model. It shows that the introduction of VIIRS in the CAMS data assimilation system enhances the accuracy of the aerosol analysis, particularly over Europe and desert and maritime sites.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
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This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
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This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Joao Carlos Martins Teixeira, Chantelle Burton, Douglas I. Kelly, Gerd A. Folberth, Fiona M. O'Connor, Richard A. Betts, and Apostolos Voulgarakis
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-136, https://doi.org/10.5194/bg-2023-136, 2023
Revised manuscript not accepted
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Representing socio-economic impacts on fires is crucial to underpin the confidence in global fire models. Introducing these into INFERNO, reduces biases and improves the modelled burnt area (BA) trends when compared to observations. Including socio-economic factors in the representation of fires in Earth System Models is important for realistically simulating BA, quantifying trends in the recent past, and for understanding the main drivers of those at regional scales.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
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We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Stefano Potter, Sol Cooperdock, Sander Veraverbeke, Xanthe Walker, Michelle C. Mack, Scott J. Goetz, Jennifer Baltzer, Laura Bourgeau-Chavez, Arden Burrell, Catherine Dieleman, Nancy French, Stijn Hantson, Elizabeth E. Hoy, Liza Jenkins, Jill F. Johnstone, Evan S. Kane, Susan M. Natali, James T. Randerson, Merritt R. Turetsky, Ellen Whitman, Elizabeth Wiggins, and Brendan M. Rogers
Biogeosciences, 20, 2785–2804, https://doi.org/10.5194/bg-20-2785-2023, https://doi.org/10.5194/bg-20-2785-2023, 2023
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Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m−2. We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.
Carolina Gallo, Jonathan M. Eden, Bastien Dieppois, Igor Drobyshev, Peter Z. Fulé, Jesús San-Miguel-Ayanz, and Matthew Blackett
Geosci. Model Dev., 16, 3103–3122, https://doi.org/10.5194/gmd-16-3103-2023, https://doi.org/10.5194/gmd-16-3103-2023, 2023
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This study conducts the first global evaluation of the latest generation of global climate models to simulate a set of fire weather indicators from the Canadian Fire Weather Index System. Models are shown to perform relatively strongly at the global scale, but they show substantial regional and seasonal differences. The results demonstrate the value of model evaluation and selection in producing reliable fire danger projections, ultimately to support decision-making and forest management.
Kandice L. Harper, Céline Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, https://doi.org/10.5194/essd-15-1465-2023, 2023
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We built a spatially explicit annual plant-functional-type (PFT) dataset for 1992–2020 exhibiting intra-class spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs, each split into leaf type and seasonality. Model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new set.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Elena Aragoneses, Mariano García, Michele Salis, Luís M. Ribeiro, and Emilio Chuvieco
Earth Syst. Sci. Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, https://doi.org/10.5194/essd-15-1287-2023, 2023
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We present a new hierarchical fuel classification system with a total of 85 fuels that is useful for preventing fire risk at different spatial scales. Based on this, we developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. We validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, we developed a crosswalk for standard fuel models as a first assignment of fuel parameters.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
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Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Yao Gao, Eleanor J. Burke, Sarah E. Chadburn, Maarit Raivonen, Mika Aurela, Lawrence B. Flanagan, Krzysztof Fortuniak, Elyn Humphreys, Annalea Lohila, Tingting Li, Tiina Markkanen, Olli Nevalainen, Mats B. Nilsson, Włodzimierz Pawlak, Aki Tsuruta, Huiyi Yang, and Tuula Aalto
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-229, https://doi.org/10.5194/bg-2022-229, 2022
Manuscript not accepted for further review
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We coupled a process-based peatland CH4 emission model HIMMELI with a state-of-art land surface model JULES. The performance of the coupled model was evaluated at six northern wetland sites. The coupled model is considered to be more appropriate in simulating wetland CH4 emission. In order to improve the simulated CH4 emission, the model requires better representation of the peat soil carbon and hydrologic processes in JULES and the methane production and transportation processes in HIMMELI.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Sebastien Garrigues, Samuel Remy, Julien Chimot, Melanie Ades, Antje Inness, Johannes Flemming, Zak Kipling, Istvan Laszlo, Angela Benedetti, Roberto Ribas, Soheila Jafariserajehlou, Bertrand Fougnie, Shobha Kondragunta, Richard Engelen, Vincent-Henri Peuch, Mark Parrington, Nicolas Bousserez, Margarita Vazquez Navarro, and Anna Agusti-Panareda
Atmos. Chem. Phys., 22, 14657–14692, https://doi.org/10.5194/acp-22-14657-2022, https://doi.org/10.5194/acp-22-14657-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating two new satellite AODs to enhance the CAMS aerosol global forecast. It highlights the spatial and temporal differences between the satellite AOD products at the model spatial resolution, which is essential information to design multi-satellite AOD data assimilation schemes.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 19, 4671–4704, https://doi.org/10.5194/bg-19-4671-2022, https://doi.org/10.5194/bg-19-4671-2022, 2022
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Soil carbon is the Earth’s largest terrestrial carbon store, and the response to climate change represents one of the key uncertainties in obtaining accurate global carbon budgets required to successfully militate against climate change. The ability of climate models to simulate present-day soil carbon is therefore vital. This study assesses soil carbon simulation in the latest ensemble of models which allows key areas for future model development to be identified.
Clement Jean Frédéric Delcourt and Sander Veraverbeke
Biogeosciences, 19, 4499–4520, https://doi.org/10.5194/bg-19-4499-2022, https://doi.org/10.5194/bg-19-4499-2022, 2022
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This study provides new equations that can be used to estimate aboveground tree biomass in larch-dominated forests of northeast Siberia. Applying these equations to 53 forest stands in the Republic of Sakha (Russia) resulted in significantly larger biomass stocks than when using existing equations. The data presented in this work can help refine biomass estimates in Siberian boreal forests. This is essential to assess changes in boreal vegetation and carbon dynamics.
Fátima Arrogante-Funes, Inmaculada Aguado, and Emilio Chuvieco
Nat. Hazards Earth Syst. Sci., 22, 2981–3003, https://doi.org/10.5194/nhess-22-2981-2022, https://doi.org/10.5194/nhess-22-2981-2022, 2022
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We show that ecological value might be reduced by 50 % due to fire perturbation in ecosystems that have not developed in the presence of fire and/or that present changes in the fire regime. The biomes most affected are tropical and subtropical forests, tundra, and mangroves. Integration of biotic and abiotic fire regime and regeneration factors resulted in a powerful way to map ecological vulnerability to fire and develop assessments to generate adaptation plans of management in forest masses.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Amar Halifa-Marín, Miguel A. Torres-Vázquez, Enrique Pravia-Sarabia, Marc Lemus-Canovas, Pedro Jiménez-Guerrero, and Juan Pedro Montávez
Hydrol. Earth Syst. Sci., 26, 4251–4263, https://doi.org/10.5194/hess-26-4251-2022, https://doi.org/10.5194/hess-26-4251-2022, 2022
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Near-natural Iberian water resources have suddenly decreased since the 1980s. These declines have been promoted by the weakening (enhancement) of wintertime precipitation (the NAOi) in the most humid areas, whereas afforestation and drought intensification have played a crucial role in semi-arid areas. Future water management would benefit from greater knowledge of North Atlantic climate variability and reforestation/afforestation processes in semi-arid catchments.
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, https://doi.org/10.5194/amt-15-4271-2022, 2022
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Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, https://doi.org/10.5194/gmd-15-5045-2022, 2022
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We developed a snow model that can be used to quantify snowpack over large areas with a high degree of spatial detail. We ran the model over the western United States, creating a snow and climate dataset for three time periods. Compared to observations of snowpack, the model captured the key aspects of snow across time and space. The model and dataset will be useful in understanding historical and future changes in snowpack, with relevance to water resources, agriculture, and ecosystems.
Joe McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Luca Cantarello, Richard Engelen, Vincent Huijnen, Antje Inness, Zak Kipling, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 5961–5981, https://doi.org/10.5194/acp-22-5961-2022, https://doi.org/10.5194/acp-22-5961-2022, 2022
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Concentrations of atmospheric methane continue to grow, in recent years at an increasing rate, for unknown reasons. Using newly available satellite observations and a state-of-the-art weather prediction model we perform global estimates of emissions from hotspots at high resolution. Results show that the system can accurately report on biases in national inventories and is used to conclude that the early COVID-19 slowdown period (March–June 2020) had little impact on global methane emissions.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Roland Vernooij, Ulrike Dusek, Maria Elena Popa, Peng Yao, Anupam Shaikat, Chenxi Qiu, Patrik Winiger, Carina van der Veen, Thomas Callum Eames, Natasha Ribeiro, and Guido R. van der Werf
Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022, https://doi.org/10.5194/acp-22-2871-2022, 2022
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Landscape fires are a major source of greenhouse gases and aerosols, particularly in sub-tropical savannas. Stable carbon isotopes in emissions can be used to trace the contribution of C3 plants (e.g. trees or shrubs) and C4 plants (e.g. savanna grasses) to greenhouse gases and aerosols if the process is well understood. This helps us to link individual vegetation types to emissions, identify biomass burning emissions in the atmosphere, and improve the reconstruction of historic fire regimes.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
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We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Tomàs Artés, Marc Castellnou, Tracy Houston Durrant, and Jesús San-Miguel
Nat. Hazards Earth Syst. Sci., 22, 509–522, https://doi.org/10.5194/nhess-22-509-2022, https://doi.org/10.5194/nhess-22-509-2022, 2022
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During the last 20 years extreme wildfires have challenged firefighting capabilities. Several fire danger indices are routinely used by firefighting services but are not suited to forecast convective extreme wildfire behaviour at the global scale. This article proposes a new fire danger index for deep moist convection, the extreme-fire behaviour index (EFBI), based on the analysis of the vertical profiles of the atmosphere above wildfires to use along with traditional fire danger indices.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
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People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
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Barnes, C., Keeping, T., Madakumbura, G., Abatzoglou, J., Williams, P., AghaKhouchak, A., Pinto, I., Thompson, V., Vautard, R., Lampe, S., Thiery, W., Pietroiusti, R., Otto, F., Vahlberg, M., Singh, R., Lambrou, N., Blakely, E., Zhu, Y., Li, J., Benmarhnia, T., Longcore, T., Marlier, M., Raju, E., Baumgart, N., and Arrighi, J.: Climate change increased the likelihood of wildfire disaster in highly exposed Los Angeles area, https://www.worldweatherattribution.org/wp-content/uploads/WWA-scientific-report-LA-wildfires-1.pdf (last access: 6 August 2025), 2025.
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Short summary
The second State of Wildfires report examines extreme wildfire events from 2024 to early 2025. It analyses key regional events in Southern California, Northeast Amazonia, Pantanal–Chiquitano, and the Congo Basin, assessing their drivers and predictability and attributing them to climate change and land use. Seasonal outlooks and decadal projections are provided. Climate change greatly increased the likelihood of these fires, and without strong mitigation, such events will become more frequent.
The second State of Wildfires report examines extreme wildfire events from 2024 to early 2025....
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